Dissertations / Theses: 'Knowledge acquisition (Expert systems)'

1

Trimble, John. "Knowledge acquisition and the system dynamics methodology." Diss., Georgia Institute of Technology, 1992. http://hdl.handle.net/1853/23337.

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2

Parsons, John Scott. "Automated knowledge acquisition for knowledge-based systems, KE-RIT : the Use of Kelleys' personal construct theory in the automation of knowledge acquisitions (theory and prototype) /." Online version of thesis, 1992. http://hdl.handle.net/1850/11056.

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3

Buck, Arlene J. "Automated knowledge acquisition tool for identification of generic tasks /." Online version of thesis, 1990. http://hdl.handle.net/1850/10577.

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4

Thorpe, Patrick J. "Knowledge acquisition for expert systems in fibre production." Thesis, Loughborough University, 1992. https://dspace.lboro.ac.uk/2134/13749.

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The aim of the study described in this thesis is to investigate the application of expert system technology to acrylic fibre production, with a particular emphasis on knowledge acquisition requirements. In doing so, it is intended to provide an understanding of the requirements and appropriate techniques for the effective application of expert systems in the process industries; The scope of the study is limited to process fault administration which involves detecting, diagnosing arid correcting abnormalities in process operation. A methodology is provided for the systematic development of expert systems within the defined area of application. An important phase in the development methodology is that of expert system specification. This involves an analysis of expert behaviour and the specification of expert system functionality: In order to assist system specification, generic knowledge types and human expert activities have been identified within the context of process fault administration. Knowledge acquisition is discussed in terms of the requirements during each phase of the proposed development methodology. A detailed review is given of the available techniques for knowledge acquisition and an assessment is presented of the most appropriate techniques to apply during each phase of the methodology. A new knowledge acquisition technique is described. The technique is designed to record knowledge of process operation and process fault diagnosis. It is based on a hierarchical decomposition of the process in terms of process objectives. Two complementary forms of knowledge representation are produced: a hierarchy diagram which shows the dependency relationships between individual process objectives and a task statement table which provides a more. detailed explanation of the objectives. Finally, three. case studies are described in which the techniques described in the thesis were applied and developed.

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5

Mitchell, F. "Painless knowledge acquisition for time series data." Thesis, University of Aberdeen, 1997. http://digitool.abdn.ac.uk/R?func=search-advanced-go&find_code1=WSN&request1=AAIU100889.

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Knowledge Acquisition has long been acknowledged as the bottleneck in producing Expert Systems. This is because, until relatively recently, the KA (Knowledge Acquisition) process has concentrated on extracting knowledge from a domain expert, which is a very time consuming process. Support tools have been constructed to help this process, but these have not been able to reduce the time radically. However, in many domains, the expert is not the only source of knowledge, nor indeed the best source of knowledge. This is particularly true in industrial settings where performance information is routinely archived. This information, if processed correctly, can provide a substantial part of the knowledge required to build a KB (Knowledge Base). In this thesis I discuss current KA approaches and then go on to outline a methodology which uses KD (Knowledge Discovery) techniques to mine archived time series data to produce fault detection and diagnosis KBs with minimal expert input. This methodology is implemented in the TIGON system, which is the focus of this thesis. TIGON uses archived information (in TIGON's case the information is from a gas turbine engine) along with guidance from the expert to produce KBs for detecting and diagnosing faults in a gas turbine engine. TIGON's performance is also analysed in some detail. A comparison with other related work is also included.

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6

Youn, Bong-Soo. "Intelligent knowledge acquisition system /." Online version of thesis, 1989. http://hdl.handle.net/1850/10444.

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7

Curtis, Gary James. "Object-oriented design for knowledge acquisition in expert systems." Thesis, University of Southampton, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.293353.

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8

Motta, Enrico. "Reusable components for knowledge modelling." N.p, 1997. http://ethos.bl.uk/.

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9

Corsar, David. "Developing knowledge-based systems through ontology mapping and ontology guided knowledge acquisition." Thesis, Available from the University of Aberdeen Library and Historic Collections Digital Resources, 2009. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?application=DIGITOOL-3&owner=resourcediscovery&custom_att_2=simple_viewer&pid=25800.

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10

Suryanto, Hendra Computer Science &amp Engineering Faculty of Engineering UNSW. "Learning and discovery in incremental knowledge acquisition." Awarded by:University of New South Wales. School of Computer Science and Engineering, 2005. http://handle.unsw.edu.au/1959.4/20744.

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Knowledge Based Systems (KBS) have been actively investigated since the early period of AI. There are four common methods of building expert systems: modeling approaches, programming approaches, case-based approaches and machine-learning approaches. One particular technique is Ripple Down Rules (RDR) which may be classified as an incremental case-based approach. Knowledge needs to be acquired from experts in the context of individual cases viewed by them. In the RDR framework, the expert adds a new rule based on the context of an individual case. This task is simple and only affects the expert???s workflow minimally. The rule added fixes an incorrect interpretation made by the KBS but with minimal impact on the KBS's previous correct performance. This provides incremental improvement. Despite these strengths of RDR, there are some limitations including rule redundancy, lack of intermediate features and lack of models. This thesis addresses these RDR limitations by applying automatic learning algorithms to reorganize the knowledge base, to learn intermediate features and possibly to discover domain models. The redundancy problem occurs because rules created in particular contexts which should have more general application. We address this limitation by reorganizing the knowledge base and removing redundant rules. Removal of redundant rules should also reduce the number of future knowledge acquisition sessions. Intermediate features improve modularity, because the expert can deal with features in groups rather than individually. In addition to the manual creation of intermediate features for RDR, we propose the automated discovery of intermediate features to speed up the knowledge acquisition process by generalizing existing rules. Finally, the Ripple Down Rules approach facilitates rapid knowledge acquisition as it can be initialized with a minimal ontology. Despite minimal modeling, we propose that a more developed knowledge model can be extracted from an existing RDR KBS. This may be useful in using RDR KBS for other applications. The most useful of these three developments was the automated discovery of intermediate features. This made a significant difference to the number of knowledge acquisition sessions required.

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11

Silveira, Gregg. "Bidding a bridge hand : a thesis on knowledge acquisition and application /." Online version of thesis, 1991. http://hdl.handle.net/1850/10936.

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12

Chan, Christine Wai-Chi. "An empirical investigation of knowledge acquisition." Thesis, University of British Columbia, 1988. http://hdl.handle.net/2429/27688.

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Expert systems are being developed despite the widely acknowledged problem of acquiring knowledge from experts. This study attempts to understand how knowledge acquisition is conducted in practice by investigating three expert system development projects. The variables examined include the expert, knowledge engineer, problem domain, organizational setting, the knowledge acquisition process, the expert system construction process, and the expert system itself. A case research methodology is adopted and data is collected through observation and taped protocol of knowledge acquisition sessions, post facto interviews with the participants involved, journalistic accounts kept by the subjects, and deliverables produced. Three cases on expert systems built in the domains of law of negligence, telephone line fault diagnostic, and wastewater treatment have been investigated. By juxtaposing the observations drawn from these cases with the findings reported in the literature, this inquiry contributes to the current understanding of the knowledge acquisition process. Business, Sauder School of Graduate

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13

Fan, Tony Chich-Chiang. "Automating knowledge acquisition for dynamic decision making in C'3I systems." Thesis, University of Cambridge, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.318319.

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14

Godfrey, Thomas James. "Extraction and representation of encyclopedic knowledge from a dictionary." Thesis, This resource online, 1993. http://scholar.lib.vt.edu/theses/available/etd-10062009-020322/.

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15

Khan, Abdus Salam Computer Science &amp Engineering Faculty of Engineering UNSW. "Incremental knowledge acquisition for case-based reasoning." Awarded by:University of New South Wales. School of Computer Science and Engineering, 2003. http://handle.unsw.edu.au/1959.4/19376.

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Case-Based Reasoning (CBR) is an appealing technique for developing intelligent systems. Besides its psycho- logical plausibility and a substantial body of research during recent years, building a good CBR system remains still a difficult task. The main problems remaining are the development of suitable case retrieval and adaptation mechanisms for CBR. The major issues are how and when to capture the necessary knowledge for both of the above aspects. As a contribution to knowledge this thesis proposes a new approach to address the experienced difficulties. The basic framework of Ripple Down Rules (RDR) is extended to allow the incremental development of a knowledge base for each of the two functions: case retrieval and case adaptation, during the use of the system while solving actual problems. The proposed approach allows an expert-user to provide explanations of why, for a given problem, certain actions should be taken. Incrementally knowledge is acquired from the expert-user in which the expert refines a rule which performs unsatisfactorily for a current given problem. The approach facilitates both, the rule acquisition as well as its validation. As a result the knowledge maintenance task of a knowledge engineer is overcome. This approach is effective with respect to both, the development of highly tailored and complex retrieval and adaptation functions for CBR as well as the provision of an intuitive and feasible approach for the expert. The approach has been implemented in a CBR system named MIKAS (Menu Construction using Incre- mental Knowledge Acquisition Systems) for the design of menus (diets) according to dietary requirements. The experimental evidence indicates the suitability of the approach to address the retrieval and adaptation problems of the menu construction domain. The experimental evidence also indicates that the difficulties of developing retrieval and adaptation functions for CBR can be effectively overcome by the proposed new approach. It is expected that the approach is likely to be useful in other problem solving domains where expert intervention is Required to modify a solution.

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16

Hasan, Irfan. "Machine learning techniques for automated knowledge acquisition in intelligent knowledge-based systems." Instructions for remote access. Click here to access this electronic resource. Access available to Kutztown University faculty, staff, and students only, 1991. http://www.kutztown.edu/library/services/remote_access.asp.

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Thesis (M.S.)--Kutztown University of Pennsylvania, 1991. Source: Masters Abstracts International, Volume: 45-06, page: 3187. Abstract precedes thesis as [2] preliminary leaves. Typescript. Includes bibliographical references (leaves 102-104).

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17

Liou, Yihwa Irene. "The use of a group decision support system environment for knowledge acquisition." Diss., The University of Arizona, 1989. http://hdl.handle.net/10150/184717.

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Knowledge acquisition is not only the most important but also most difficult task knowledge engineers face when they begin to develop expert systems. One of the first problems they encounter is the need to identify at least one individual with appropriate expertise who is able and willing to participate in the development project. They must also be able to use a variety of techniques to elicit the knowledge that they require. These include such traditional knowledge acquisition methods as interviewing, thinking-aloud protocol analysis, on-site observation, and repertory grid analysis. As expert system applications have become more complex, knowledge engineers have found that they must work with and tap the domain knowledge of not one but several individuals. They have also discovered that the traditional methods do not work well in eliciting the knowledge residing in a group of individuals. The complexity of the systems, the difficulties inherent in working with multiple experts, and the lack of appropriate tools have combined to make the knowledge acquisition task even more arduous and time consuming. Group Decision Support Systems (GDSS) have been proven to be useful tools for improving the efficiency and effectiveness of a multiplicity of group activities. It would appear that by bringing experts together in a GDSS environment and using computer-based tools to facilitate group interaction and information exchange, a knowledge engineer could eliminate many of these problems. This research was designed to explore the possibility of using a GDSS environment to facilitate knowledge acquisition from multiple experts. The primary research question was "Does A GDSS environment facilitate the acquisition of knowledge from multiple experts?" The principle contributions of this research are (1) demonstration of the first use of a GDSS environment to elicit knowledge from multiple experts; (2) establishment of a methodology for knowledge acquisition in a GDSS environment; (3) development of process models for acquiring knowledge; (4) development of guidelines for designing and evaluating group support tools; and (5) recognition of some implications of using a computer-supported cooperative approach to extract knowledge from a group of experts. (Abstract shortened with permission of author.)

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18

Emero, Michael F. "Using naturally occurring texts as a knowledge acquisition resource for knowledge base design : developing a knowledge base taxonomy on microprocessors /." Master's thesis, This resource online, 1992. http://scholar.lib.vt.edu/theses/available/etd-02162010-020204/.

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19

Plant, Robert T. "A methodology for knowledge acquisition in the development of expert systems." Thesis, University of Liverpool, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.240378.

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20

Erdani, Yuliadi. "Acquisition of Human Expert Knowledge for Rule-based Knowledge-based Systems using Ternary Grid." Gerhard-Mercator-Universitaet Duisburg, 2005. http://www.ub.uni-duisburg.de/ETD-db/theses/available/duett-06282005-101136/.

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Knowledge acquisition is the most important part in the development of expert system. It deals with extracting knowledge from sources of expertise and transferring it to a knowledge base. Knowledge acquisition is major research field in knowledge engineering and still the most difficult and error-prone task for knowledge engineer while building an expert system. This situation influences the performance of the knowledge due to the quality of information and the reduction of error possibility. It is not an easy task to acquire knowledge from human expert not trained in knowledge engineering. The performance of the knowledge is performed by interaction between experts and knowledge engineer or machine during acquisition process. In most rule-based expert system, building of rules can easily be done. Knowledge Engineer or expert does not have to do any work specifying rules and how they are linked to each other. Sometime the knowledge engineer or expert can reference rules or facts that have not yet been created. It seems to be a simple and an instant work. The problem due to the performance of the knowledge will not occur until the number of rules is getting higher. Some problem may appear in the form of inconsistent rules, unreachable rules, redundant rule and rotating chain of rules. In order to solve that problem and to achieve that mentioned performance, a rule-based knowledge acquisition system using Ternary Grid is developed. This system acquires knowledge from human expert using grid or matrix system. Ternary Grid represents a model of rule-based knowledge in a grid or matrix format.

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21

Jafar, Musa Jafar. "A tool for interactive verification and validation of rule-based expert systems." Diss., The University of Arizona, 1989. http://hdl.handle.net/10150/184805.

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Interactive as well as Automatic Verification and Validation is valuable, especially when the size of a knowledge base grows and manual techniques are not feasible. It ensures the stability of the system and raises the confidence in its level of performance. In this dissertation I address the problem of verification and validation of rule based expert systems. It is a problem knowledge engineers have to deal with while building their expert systems to ensure the reliability, accuracy, and completeness of their knowledge bases. The objective of this research is to make it easy for expert systems developers to build the right system by proposing practical and simple methods for building verification and validation programs to insure the integrity and performance of large scale knowledge based systems.

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22

Richardson, Matthew. "Learning and inference in collective knowledge bases /." Thesis, Connect to this title online; UW restricted, 2004. http://hdl.handle.net/1773/6926.

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23

Nikiforou, Savvas. "Selection of Clinical Trials: Knowledge Representation and Acquisition." Scholar Commons, 2002. https://scholarcommons.usf.edu/etd/1527.

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When medical researchers test a new treatment procedure, they recruit patients with appropriate health problems and medical histories. An experiment with a new procedure is called a clinical trial. The selection of patients for clinical trials has traditionally been a labor-intensive task, which involves matching of medical records with a list of eligibility criteria. A recent project at the University of South Florida has been aimed at the automation of this task. The project has involved the development of an expert system that selects matching clinical trials for each patient. If a patient's data are not sufficient for choosing a trial, the system suggests additional medical tests. We report the work on the representation and entry of the related selection criteria and medical tests. We first explain the structureof the system's knowledge base, which describes clinical trials and criteria for selecting patients. We then present an interface that enables a clinician to add new trials and selection criteria without the help of a programmer. Experiments show that the addition of a new clinical trial takes ten to twenty minutes, and that novice users learn the full functionality of the interface in about an hour.

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24

Chronister, Julie Anne. "A domain-independent framework for structuring knowledge in the OFMspert architecture." Thesis, Georgia Institute of Technology, 1990. http://hdl.handle.net/1853/25752.

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25

Trybula, Walt. "Text mining and knowledge discernment : an exploratory investigation /." Digital version accessible at:, 1999. http://wwwlib.umi.com/cr/utexas/main.

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26

Connor, James W. "ESKAPE/CF : a knowledge acquisition tool for expert systems using cognitive feedback." Thesis, Monterey, California. Naval Postgraduate School, 1991. http://hdl.handle.net/10945/28173.

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27

Rojo, Vicente Guerrero. "MML, a modelling language with dynamic selection of methods." Thesis, University of Sussex, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.285103.

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28

Pham, Son Bao Computer Science &amp Engineering Faculty of Engineering UNSW. "Incremental knowledge acquisition for natural language processing." Awarded by:University of New South Wales. School of Computer Science and Engineering, 2006. http://handle.unsw.edu.au/1959.4/26299.

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Linguistic patterns have been used widely in shallow methods to develop numerous NLP applications. Approaches for acquiring linguistic patterns can be broadly categorised into three groups: supervised learning, unsupervised learning and manual methods. In supervised learning approaches, a large annotated training corpus is required for the learning algorithms to achieve decent results. However, annotated corpora are expensive to obtain and usually available only for established tasks. Unsupervised learning approaches usually start with a few seed examples and gather some statistics based on a large unannotated corpus to detect new examples that are similar to the seed ones. Most of these approaches either populate lexicons for predefined patterns or learn new patterns for extracting general factual information; hence they are applicable to only a limited number of tasks. Manually creating linguistic patterns has the advantage of utilising an expert's knowledge to overcome the scarcity of annotated data. In tasks with no annotated data available, the manual way seems to be the only choice. One typical problem that occurs with manual approaches is that the combination of multiple patterns, possibly being used at different stages of processing, often causes unintended side effects. Existing approaches, however, do not focus on the practical problem of acquiring those patterns but rather on how to use linguistic patterns for processing text. A systematic way to support the process of manually acquiring linguistic patterns in an efficient manner is long overdue. This thesis presents KAFTIE, an incremental knowledge acquisition framework that strongly supports experts in creating linguistic patterns manually for various NLP tasks. KAFTIE addresses difficulties in manually constructing knowledge bases of linguistic patterns, or rules in general, often faced in existing approaches by: (1) offering a systematic way to create new patterns while ensuring they are consistent; (2) alleviating the difficulty in choosing the right level of generality when creating a new pattern; (3) suggesting how existing patterns can be modified to improve the knowledge base's performance; (4) making the effort in creating a new pattern, or modifying an existing pattern, independent of the knowledge base's size. KAFTIE, therefore, makes it possible for experts to efficiently build large knowledge bases for complex tasks. This thesis also presents the KAFDIS framework for discourse processing using new representation formalisms: the level-of-detail tree and the discourse structure graph.

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29

Joseph, Anton T. "Knowledge acquisition and implementation in an expert process planning system." Thesis, University of Manchester, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.346428.

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30

Kotnour, Timothy G. "Design, development, and testing of an automated knowledge-acquisition tool to aid problem solving, decision making, and planning." Thesis, This resource online, 1992. http://scholar.lib.vt.edu/theses/available/etd-12302008-063800/.

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31

Gupta, Chaitali. "Web services query matchmaking with automated knowledge acquisition." Diss., Online access via UMI:, 2007.

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32

Fraser, Pierre. "Pistes d'exploration pour l'élaboration d'un système formel de montée en abstraction et d'émergence de catégorisations linguistiques /." Thèse, Chicoutimi : Université du Québec à Chicoutimi, 2001. http://theses.uqac.ca.

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33

Whetzel, Jonathan Hunt. "Developing intelligent agents for training systems that learn their strategies from expert players." Texas A&M University, 2005. http://hdl.handle.net/1969.1/2662.

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Computer-based training systems have become a mainstay in military and private institutions for training people how to perform certain complex tasks. As these tasks expand in difficulty, intelligent agents will appear as virtual teammates or tutors assisting a trainee in performing and learning the task. For developing these agents, we must obtain the strategies from expert players and emulate their behavior within the agent. Past researchers have shown the challenges in acquiring this information from expert human players and translating it into the agent. A solution for this problem involves using computer systems that assist in the human expert knowledge elicitation process. In this thesis, we present an approach for developing an agent for the game Revised Space Fortress, a game representative of the complex tasks found in training systems. Using machine learning techniques, the agent learns the strategy for the game by observing how a human expert plays. We highlight the challenges encountered while designing and training the agent in this real-time game environment, and our solutions toward handling these problems. Afterward, we discuss our experiment that examines whether trainees experience a difference in performance when training with a human or virtual partner, and how expert agents that express distinctive behaviors affect the learning of a human trainee. We show from our results that a partner agent that learns its strategy from an expert player serves the same benefit as a training partner compared to a programmed expert-level agent and a human partner of equal intelligence to the trainee.

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34

Huber, Bernard J. Jr. "A knowledge-based approach to understanding natural language. /." Online version of thesis, 1991. http://hdl.handle.net/1850/11053.

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35

Bhandari, Archna. "Enhancements to the frame virtual machine /." Online version of thesis, 1989. http://hdl.handle.net/1850/10581.

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36

Boulis, Constantinos. "Topic learning in text and conversational speech /." Thesis, Connect to this title online; UW restricted, 2005. http://hdl.handle.net/1773/5914.

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37

Vazey, Megan Margaret. "Case-driven collaborative classification." Doctoral thesis, Australia : Macquarie University, 2007. http://hdl.handle.net/1959.14/264.

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Thesis (PhD) -- Macquarie University, Division of Information and Communication Sciences, Department of Computing, 2007. "Submitted January 27 2007, revised July 27 2007". Bibliography: p. 281-304. Mode of access: World Wide Web. xiv, 487 p., bound ill. (some col.)

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38

Song, Xiaodan. "Exploiting dynamic patterns for recommendation systems /." Thesis, Connect to this title online; UW restricted, 2006. http://hdl.handle.net/1773/5833.

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39

Burge, Janet E. "Knowledge Elicitation for Design Task Sequencing Knowledge." Digital WPI, 1999. https://digitalcommons.wpi.edu/etd-theses/1062.

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"There are many types of knowledge involved in producing a design (the process of specifying a description of an artifact that satisfies a collection of constraints [Brown, 1992]). Of these, one of the most crucial is the design plan: the sequence of steps taken to create the design (or a portion of the design). A number of knowledge elicitation methods can be used to obtain this knowledge from the designer. The success of the elicitation depends on the match between the knowledge elicitation method used and the information being sought. The difficulty with obtaining design plan information is that this information may involve implicit knowledge, i.e. knowledge that can not be expressed explicitly. In this thesis, an approach is used that combines two knowledge elicitation techniques: one direct, to directly request the design steps and their sequence, and one indirect, to refine this knowledge by obtaining steps and sequences that may be implicit. The two techniques used in this thesis were Forward Scenario Simulation (FSS), a technique where the domain expert describes how the procedure followed to solve it, and Card Sort, a technique where the domain expert is asked to sort items (usually entities in the domain) along different attributes. The Design Ordering Elicitation System (DOES) was built to perform the knowledge elicitation. This system is a web-based system designed to support remote knowledge elicitation: KE performed without the presence of the knowledge engineer. This system was used to administer knowledge elicitation sessions to evaluate the effectiveness of these techniques at obtaining design steps and their sequencing. The results indicate that using an indirect technique together with a direct technique obtains more alternative sequences for the design steps than using the direct technique alone."

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40

Sun, Xingzhi. "Knowledge discovery in long temporal event sequences /." [St. Lucia, Qld.], 2005. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe18601.pdf.

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41

Zhang, Aining Carleton University Dissertation Geography. "Knowledge acquisition and system design for an expert advisory system for statistical analysis (EASSA) for electronic mapping and geographical information systems." Ottawa, 1991.

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42

Nasuti, Frank W. "Knowledge Acquisition using Multiple Domain Experts in the Design and Development of an Expert System for Disaster Recovery Planning." NSUWorks, 2000. http://nsuworks.nova.edu/gscis_etd/746.

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The increasing dependence of organizations on data processing to perform the basic functions of corporate America, together with recent disasters such as earthquakes, tornadoes and hurricanes have awakened management to the realization that they require Disaster Recovery Plans (DRP) and Business Resumption Services (BRS). To address these needs, organizations frequently consult with outsiders to help them develop disaster recovery and business resumption plans. Although consultants and vendors specializing in disaster recovery planning are available, their number is limited and the quality of their services may be questionable. In addition, the information gathering process by consultants is a time consuming process and in most cases requires the use of multiple vendor experts, as well as various resources within the customer's organization. This research proposed, as a solution to address these deficiencies, the design and development of an expert system to assist in the determination of the needs of an organization for disaster recovery and business resumption services, as well as the evaluation of existing plans. This research resulted in the design of an expert system for disaster recovery planning. It included the knowledge acquisition processes necessary to elicit information from multiple domain experts. The specific goals of this research were: (1) knowledge acquisition specific to the problems of using multiple domain experts; (2) design and development of a prototype expert system for disaster recovery planning; and (3) validation of the prototype expert system.

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43

Carton, Patrice. "Acquisition et reconnaissance de messages graphiques, un systeme expert dans un systeme eao." Paris 6, 1988. http://www.theses.fr/1988PA066121.

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Apres l'analyse des principales composantes du dialogue graphique mettent en relation un auteur et un apprenant par l'intermediaire d'un didacticiel, la representation et la manipulaption des objets graphiques sont abordees sous leurs deux aspects indissociables, production et reconnaissance

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44

Tecuci, Gheorghe. "Disciple : a theory, methodology and system for learning expert knowledge." Paris 11, 1988. http://www.theses.fr/1988PA112209.

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DISCIPLE est un système qui illustre une théorie et une méthodologie d'apprentissage des connaissances expertes. Il est composé d'un système expert et d'un système d'apprentissage qui utilise une même base de connaissances. DISCIPLE part de connaissances élémentaires sur un domaine d'application (une théorie du domaine) et, au cours de sessions interactives de résolution de problèmes, apprend de règles générales à partir des solutions spécifiques fournies par l'expert humain. La méthode de résolution de problèmes combine la réduction de problèmes, l'utilisation de contraintes et l'analogie. Quant à l'apprentissage, DISCIPLE utilise différentes méthodes, en fonction de ses connaissances sur la solution de l'utilisateur. Cette solution est considérée comme un exemple pour apprendre une règle générale. Dans le cas d'une théorie complète sur l'exemple, DISCIPLE apprend à partir d'explications, ce qui augmente son efficacité. Dans le cas d'une théorie faible, il intègre l'apprentissage à partir d'explications, l'apprentissage par analogie et l'apprentissage empirique, développant ainsi sa compétence. Enfin, dans le cas d'une théorie incomplète, il apprend en combinant les deux méthodes précédentes, ce qui améliore tant sa compétence que son efficacité This thesis presents DISCIPLE, a system illustrating a theory and a methodology for learning expert knowledge. DISCIPLE integrates a learning system and an empty expert system, both using the same knowledge base. It is provided with an initial domain theory and learns problem solving rules from the problem solving steps received from its expert user, during interactive problem solving sessions. In this way, DISCIPLE evolves from a helpful assistant in problem solving to a genuine expert. The problem solving method of DISCIPLE combines problem reduction, problem solving by constraints, and problem solving by analogy. The learning method of DISCIPLE depends of its knowledge about the problem solving step (the example) from which it learns. In the context of a complete theory about the example, DISCIPLE uses explanation based learning to improve its performance. In the context of a weak theory about the example, it synergistically combines explanation - based learning, learning by analogy, and empirical learning, developing its competence. In the context of an incomplete theory about the example, DISCIPLE learns by Combining the above mentioned methods, improving both its competence and performance

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Gao, Yongchun 1977. "The application of Web Ontology Language for information sharing in the dairy industry /." Thesis, McGill University, 2005. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=97957.

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In this thesis the Semantic Web and its core technology---Web Ontology Language (OWL)---were studied. Considering the features of the different units involved in the dairy industry, OWL, in its capacity as an ontology description language, can be used to encode and thus exchange ontology among the units in the dairy industry. After creation of OWL file using Protege, an OWL parser was programmed to decode the ontology and data contained in the OWL file. Based on these investigations, it was determined that OWL can be used to encode, exchange, and decode data between farms and the units that interact with them, although large volumes of data among the service agencies pose certain challenges in terms of transfer size. A structure of the Semantic Web services in the dairy industry is proposed for Semantic Web Service registration, search and usage related to certain farm-management tasks. With the help of the Semantic Web and OWL, one can expect a more efficient data processing in the future dairy industry.

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Schiavini, Marcos Melo. "Ferramenta de aquisição de conhecimento por modelos explicitos." [s.n.], 1991. http://repositorio.unicamp.br/jspui/handle/REPOSIP/259552.

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Orientador: Marcio Luiz de Andrade Netto Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica Made available in DSpace on 2018-07-13T23:17:40Z (GMT). No. of bitstreams: 1 Schiavini_MarcosMelo_M.pdf: 13404383 bytes, checksum: fe85c025b2fd3ced855421c365c05348 (MD5) Previous issue date: 1991 Resumo: A tese apresenta uma contribuição para agilizar e organizar o processo de aquisição de conhecimento necessário ao desenvolvimento de sistemas Especialistas. Para tanto é descrita uma ferramenta computacional de auxilio ao processo de aquisição e engenharia de conhecimento - CAKE - que emprega um modelo do domínio durante sua interação com o especialista. O modelo é elaborado e representado com o auxílio do KADS, uma metodologia de construção de sistemas baseados em conhecimento [WIELINGA 89]. Com esse trabalho visamos obter uma ferramenta de aquisição de conhecimento que não apenas apresente as vantagens de empregar um modelo como também não tenha seu uso limitado a apenas um domínio particular. Para tanto concebemos uma ferramenta que deixa explícito o modelo utilizado para guiar o processo de aquisição de conhecimento. O engenheiro do conhecimento pode alterar a ferramenta para adequá-la às suas necessidades Abstract: The theses presents a contribution to facilitate and to organize the knowledge acquisition process necessary in the development of Expert Systems. A computer aided knowledge acquisition and engineering tool - CAKE -that employs a domain model in its interaction with the expert is proposed. The model is constructed and represented with the help of KADS, a methodology to construct knowledge based systems [WIELINGA 89]. It is intended, with this work, to obtain a knowledge acquisition tool that not only has the advantages of using a model, but also does not have its applicability limited to a particular domain. For this purpose, we have conceived a tool that leaves explicit the model used in guiding the knowledge acquisition processo The knowledge engineer is able to modify the tool to make the necessary adaptations for his further needs Mestrado Mestre em Engenharia Elétrica

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Strobel, Johannes M. J. "Historical reasoning with a cognitive flexibility hypertext authoring system : an explorative study on the role of epistemological beliefs on advanced knowledge acquisition /." free to MU campus, to others for purchase, 2004. http://wwwlib.umi.com/cr/mo/fullcit?p3164544.

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Barkowsky, Thomas. "Mental representation and processing of geographic knowledge : a computational approach /." Berlin [u.a.] : Springer, 2002. http://www.loc.gov/catdir/enhancements/fy0817/2002042843-d.html.

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Gréboval, Catherine. "Aide : une approche et une architecture pour rendre opérationnels des modèles conceptuels." Compiègne, 1992. http://www.theses.fr/1992COMP0525.

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Afin de combiner l'apport des modèles conceptuels pour l'aide à l'acquisition des connaissances, et l'apport des systèmes experts de seconde génération pour concevoir des résolveurs de problèmes plus robustes et plus faciles à expliquer, nous proposons une approche consistant à rendre opérationnels des modèles conceptuels. Cette approche repose sur le générateur (shell) AIDE qui permet à l'ingénieur de la connaissance de modéliser à un haut niveau d'abstraction. Le générateur est basé sur un mécanisme de traduction pour coder automatiquement le modèle conceptuel, complètement formalisé en un modèle de plus bas niveau, directement exécutable. De cette façon, le lien entre le modèle conceptuel et le système informatique est conservé. Outre les avantages liés au prototypage au niveau connaissance, l'approche AIDE permet ainsi de valider et d'expliquer à ce même haut niveau d'abstraction. Le système de diagnostic médical SATIN a permis de fournir une première validation du générateur AIDE

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Kmelnitsky, Vitaly M. "Automated On-line Diagnosis and Control Configuration in Robotic Systems Using Model Based Analytical Redundancy." Digital WPI, 2002. https://digitalcommons.wpi.edu/etd-theses/167.

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Because of the increasingly demanding tasks that robotic systems are asked to perform, there is a need to make them more reliable, intelligent, versatile and self-sufficient. Furthermore, throughout the robotic system?s operation, changes in its internal and external environments arise, which can distort trajectory tracking, slow down its performance, decrease its capabilities, and even bring it to a total halt. Changes in robotic systems are inevitable. They have diverse characteristics, magnitudes and origins, from the all-familiar viscous friction to Coulomb/Sticktion friction, and from structural vibrations to air/underwater environmental change. This thesis presents an on-line environmental Change, Detection, Isolation and Accommodation (CDIA) scheme that provides a robotic system the capabilities to achieve demanding requirements and manage the ever-emerging changes. The CDIA scheme is structured around a priori known dynamic models of the robotic system and the changes (faults). In this approach, the system monitors its internal and external environments, detects any changes, identifies and learns them, and makes necessary corrections into its behavior in order to minimize or counteract their effects. A comprehensive study is presented that deals with every stage, aspect, and variation of the CDIA process. One of the novelties of the proposed approach is that the profile of the change may be either time or state-dependent. The contribution of the CDIA scheme is twofold as it provides robustness with respect to unmodeled dynamics and with respect to torque-dependent, state-dependent, structural and external environment changes. The effectiveness of the proposed approach is verified by the development of the CDIA scheme for a SCARA robot. Results of this extensive numerical study are included to verify the applicability of the proposed scheme.

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